Merge branch 'release_v1.0.0' into 'master'

Resolve "new release v1.0.0"

Closes #188

See merge request toar/mlair!162

.gitlab-ci.yml

@@ -43,7 +43,7 @@ tests (from scratch):
   script:
     - zypper --non-interactive install binutils libproj-devel gdal-devel
     - zypper --non-interactive install proj geos-devel
-    - pip install -r requirements.txt
+    - cat requirements.txt | cut -f1 -d"#" | sed '/^\s*$/d' | xargs -L 1 pip install
     - chmod +x ./CI/run_pytest.sh
     - ./CI/run_pytest.sh
   after_script:

CHANGELOG.md

 # Changelog
 All notable changes to this project will be documented in this file.
 
+## v1.0.0 -  2020-10-08  - official release of new version 1.0.0
+
+### general:
+- This is the first official release of MLAir ready for use
+- updated license, installation instruction
+
+### technical:
+- restructured order of packages in requirements
+
+## v0.12.2 -  2020-10-01  - HDFML support
+
+### general:
+- HDFML support
+
+### technical:
+- installation script for HDFML adjusted, #183
 
 ## v0.12.1 -  2020-09-28  - examples in notebook
 

LICENSE

 MIT License
 
-Copyright (c) 2020 Lukas Leufen
+Copyright (c) 2020 Forschungszentrum Jülich GmbH
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -10,32 +10,86 @@ docs [here](http://toar.pages.jsc.fz-juelich.de/mlair/docs/).
 
 MLAir is based on several python frameworks. To work properly, you have to install all packages from the 
 `requirements.txt` file. Additionally to support the geographical plotting part it is required to install geo
-packages built for your operating system. Name names of these package may differ for different systems, we refer
-here to the opensuse / leap OS. The geo plot can be removed from the `plot_list`, in this case there is no need to 
-install the geo packages. For special instructions to install MLAir on the Juelich HPC systems, see 
-[here](#special-instructions-for-installation-on-jülich-hpc-systems).
-
-* (geo) Install **proj** on your machine using the console. E.g. for opensuse / leap `zypper install proj`
-* (geo) A c++ compiler is required for the installation of the program **cartopy**
-* Install all requirements from [`requirements.txt`](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/requirements.txt)
-  preferably in a virtual environment
-* (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't
-  find any compatibility errors. Please note, that tf-1.13 and 1.15 have two distinct branches each, the default branch 
-  for CPU support, and the "-gpu" branch for GPU support. If the GPU version is installed, MLAir will make use of the GPU
-  device.
+packages built for your operating system. Unfortunately, the names of these package may differ for different systems.
+In this instruction, we try to address users of different operating systems namely openSUSE Leap, Ubuntu and macOS.
+If the installation is still not working, we recommend skipping the geographical plot. We have put together a small 
+workaround [here](#workaround-to-skip-geographical-plot). For special instructions to install MLAir on the Juelich 
+HPC systems, see [here](#special-instructions-for-installation-on-jülich-hpc-systems).
+
+* Make sure to have the **python3.6** version installed.
+* (geo) A **c++ compiler** is required for the installation of the program **cartopy**
+* (geo) Install **proj** and **GEOS** on your machine using the console.
+* Install the **python3.6 develop** libraries.
+* Install all **requirements** from [`requirements.txt`](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/requirements.txt)
+  preferably in a virtual environment. You can use `pip install -r requirements.txt` to install all requirements at 
+  once. Note, we recently updated the version of Cartopy and there seems to be an ongoing 
+  [issue](https://github.com/SciTools/cartopy/issues/1552) when installing numpy and Cartopy at the same time. If you
+  run into trouble, you could use `cat requirements.txt | cut -f1 -d"#" | sed '/^\s*$/d' | xargs -L 1 pip install` 
+  instead.
 * Installation of **MLAir**:
     * Either clone MLAir from the [gitlab repository](https://gitlab.version.fz-juelich.de/toar/mlair.git) 
       and use it without installation (beside the requirements) 
-    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-0.12.2-py3-none-any.whl)) 
+    * or download the distribution file ([current version](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.0.0-py3-none-any.whl)) 
       and install it via `pip install <dist_file>.whl`. In this case, you can simply import MLAir in any python script 
       inside your virtual environment using `import mlair`.
+* (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't
+  find any compatibility errors. Please note, that tf-1.13 and 1.15 have two distinct branches each, the default branch 
+  for CPU support, and the "-gpu" branch for GPU support. If the GPU version is installed, MLAir will make use of the GPU
+  device.
+
+## openSUSE Leap 15.1
+
+* c++ compiler
+
+`sudo zypper install gcc-c++`
+
+* geo packages
+
+`sudo zypper install proj geos-devel`
+
+* depending on the pre-installed packages it could be required to install further packages
+
+`sudo zypper install libproj-devel binutils gdal-devel graphviz`
+
+* python develop libraries
+
+`sudo zypper install python3-devel`
+
+## Ubuntu 20.04.1
+
+* c++ compiler
 
+`sudo apt install build-essential` 
+
+* geo packages
+
+`sudo apt install proj-bin libgeos-dev libproj-dev`
+
+* depending on the pre-installed packages it could be required to install further packages
+
+`sudo apt install graphviz libgeos++-dev`
+
+* python develop libraries
+
+`sudo apt install python3.6-dev`
+
+## macOS & windows
+
+The installation on macOS is not tested yet. The following commands are possibly needed:
+
+`brew install geos`
+
+`sudo port install graphviz`
+
+The installation on Windows is not tested yet.
 
 # How to start with MLAir
 
 In this section, we show three examples how to work with MLAir. Note, that for these examples MLAir was installed using
 the distribution file. In case you are using the git clone it is required to adjust the import path if not directly
-executed inside the source directory of MLAir.
+executed inside the source directory of MLAir. There is also a downloadable 
+[Jupyter Notebook](https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/supplement/Examples_from_manuscript.ipynb) 
+provided in that you can run the following examples. Note that this notebook still requires an installation of MLAir.
 
 ## Example 1
 
@@ -421,6 +475,20 @@ class DummyDataHandler(AbstractDataHandler):
 
 # Special Remarks
 
+## Workaround to skip geographical plot
+
+If it is not possible to install all required geo libraries on your system, a good compromise is to skip the creation
+of the geographical plot. Therefore, it is required to remove the plot from the `plot_list` manually. We recommend to
+use this code snippet as a starting point.
+
+```python
+from mlair.helpers import remove_items
+from mlair.configuration.defaults import DEFAULT_PLOT_LIST
+
+mlair.run(plot_list=remove_items(DEFAULT_PLOT_LIST, "PlotStationMap"))
+
+```
+
 ## Special instructions for installation on Jülich HPC systems
 
 _Please note, that the HPC setup is customised for JUWELS and HDFML. When using another HPC system, you can use the HPC 
@@ -429,10 +497,10 @@ setup files as a skeleton and customise it to your needs._
 The following instruction guide you through the installation on JUWELS and HDFML. 
 * Clone the repo to HPC system (we recommend to place it in `/p/projects/<project name>`).
 * Setup venv by executing `source setupHPC.sh`. This script loads all pre-installed modules and creates a venv for 
-all other packages. Furthermore, it creates slurm/batch scripts to execute code on compute nodes. <br> 
+all other packages. Furthermore, it creates slurm/batch scripts to execute code on compute nodes.
 You have to enter the HPC project's budget name (--account flag).
 * The default external data path on JUWELS and HDFML is set to `/p/project/deepacf/intelliaq/<user>/DATA/toar_<sampling>`. 
-<br>To choose a different location open `run.py` and add the following keyword argument to `ExperimentSetup`: 
+To choose a different location open `run.py` and add the following keyword argument to `ExperimentSetup`: 
 `data_path=<your>/<custom>/<path>`. 
 * Execute `python run.py` on a login node to download example data. The program will throw an OSerror after downloading.
 * Execute either `sbatch run_juwels_develgpus.bash` or `sbatch run_hdfml_batch.bash` to verify that the setup went well.

docs/_source/get-started.rst

@@ -11,19 +11,19 @@ Install MLAir
 
 MLAir is based on several python frameworks. To work properly, you have to install all packages from the
 :py:`requirements.txt` file. Additionally to support the geographical plotting part it is required to install geo
-packages built for your operating system. Name names of these package may differ for different systems, we refer
-here to the opensuse / leap OS. The geo plot can be removed from the :py:`plot_list`, in this case there is no need to
-install the geo packages.
+packages built for your operating system. Unfortunately, the names of these package may differ for different systems.
+In this instruction, we try to address users of different operating systems namely openSUSE Leap, Ubuntu and macOS.
+If the installation is still not working, we recommend skipping the geographical plot. We have put together a small
+workaround :ref:`here<Workaround to skip geographical plot>`. For special instructions to install MLAir on the Juelich
+HPC systems, see section :ref:`Installation on Jülich HPC systems`.
 
 Pre-requirements
 ~~~~~~~~~~~~~~~~
 
-* (geo) Install **proj** on your machine using the console. E.g. for opensuse / leap :py:`zypper install proj`
-* (geo) A c++ compiler is required for the installation of the program **cartopy**
-* (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't
-  find any compatibility errors. Please note, that tf-1.13 and 1.15 have two distinct branches each, the default branch
-  for CPU support, and the "-gpu" branch for GPU support. If the GPU version is installed, MLAir will make use of the GPU
-  device.
+* Make sure to have the **python3.6** version installed.
+* (geo) A **c++ compiler** is required for the installation of the program **cartopy**
+* (geo) Install **proj** and **GEOS** on your machine using the console.
+* Install the **python3.6 develop** libraries.
 
 Installation of MLAir
 ~~~~~~~~~~~~~~~~~~~~~
@@ -31,9 +31,103 @@ Installation of MLAir
 * Install all requirements from `requirements.txt <https://gitlab.version.fz-juelich.de/toar/machinelearningtools/-/blob/master/requirements.txt>`_
   preferably in a virtual environment
 * Either clone MLAir from the `gitlab repository <https://gitlab.version.fz-juelich.de/toar/machinelearningtools.git>`_
-* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-0.12.2-py3-none-any.whl>`_)
+* or download the distribution file (`current version <https://gitlab.version.fz-juelich.de/toar/mlair/-/blob/master/dist/mlair-1.0.0-py3-none-any.whl>`_)
   and install it via :py:`pip install <dist_file>.whl`. In this case, you can simply
   import MLAir in any python script inside your virtual environment using :py:`import mlair`.
+* (tf) Currently, TensorFlow-1.13 is mentioned in the requirements. We already tested the TensorFlow-1.15 version and couldn't
+  find any compatibility errors. Please note, that tf-1.13 and 1.15 have two distinct branches each, the default branch
+  for CPU support, and the "-gpu" branch for GPU support. If the GPU version is installed, MLAir will make use of the GPU
+  device.
+
+Special Instructions for Installation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+openSUSE Leap 15.1
+""""""""""""""""""
+
+* c++ compiler
+
+:py:`sudo zypper install gcc-c++`
+
+* geo packages
+
+:py:`sudo zypper install proj geos-devel`
+
+* depending on the pre-installed packages it could be required to install further packages
+
+:py:`sudo zypper install libproj-devel binutils gdal-devel graphviz`
+
+* python develop libraries
+
+:py:`sudo zypper install python3-devel`
+
+Ubuntu 20.04.1
+""""""""""""""
+
+* c++ compiler
+
+:py:`sudo apt install build-essential`
+
+* geo packages
+
+:py:`sudo apt install proj-bin libgeos-dev libproj-dev`
+
+* depending on the pre-installed packages it could be required to install further packages
+
+:py:`sudo apt install graphviz libgeos++-dev`
+
+* python develop libraries
+
+:py:`sudo apt install python3.6-dev`
+
+macOS & windows
+"""""""""""""""
+
+The installation on macOS is not tested yet. The following commands are possibly needed:
+
+:py:`brew install geos`
+
+:py:`sudo port install graphviz`
+
+The installation on Windows is not tested yet.
+
+Installation on Jülich HPC systems
+""""""""""""""""""""""""""""""""""
+
+*Please note, that the HPC setup is customised for JUWELS and HDFML. When using another HPC system, you can use the HPC
+setup files as a skeleton and customise it to your needs.*
+
+The following instruction guide you through the installation on JUWELS and HDFML.
+
+* Clone the repo to HPC system (we recommend to place it in :py:`/p/projects/<project name>`).
+* Setup venv by executing :py:`source setupHPC.sh`. This script loads all pre-installed modules and creates a venv for
+  all other packages. Furthermore, it creates slurm/batch scripts to execute code on compute nodes.
+  You have to enter the HPC project's budget name (--account flag).
+* The default external data path on JUWELS and HDFML is set to :py:`/p/project/deepacf/intelliaq/<user>/DATA/toar_<sampling>`.
+* To choose a different location open :py:`run.py` and add the following keyword argument to :py:`ExperimentSetup`:
+  :py:`data_path=<your>/<custom>/<path>`.
+* Execute :py:`python run.py` on a login node to download example data. The program will throw an OSerror after downloading.
+* Execute either :py:`sbatch run_juwels_develgpus.bash` or :py:`sbatch run_hdfml_batch.bash` to verify that the setup
+  went well.
+* Currently cartopy is not working on our HPC system, therefore PlotStations does not create any output.
+
+Note: The method :py:`PartitionCheck` currently only checks if the hostname starts with :py:`ju` or :py:`hdfmll`.
+Therefore, it might be necessary to adopt the :py:`if` statement in :py:`PartitionCheck._run`.
+
+
+Workaround to skip geographical plot
+""""""""""""""""""""""""""""""""""""
+
+If it is not possible to install all required geo libraries on your system, a good compromise is to skip the creation
+of the geographical plot. Therefore, it is required to remove the plot from the :py:`plot_list` manually. We recommend
+to use this code snippet as a starting point.
+
+.. code-block:: python
+
+    from mlair.helpers import remove_items
+    from mlair.configuration.defaults import DEFAULT_PLOT_LIST
+
+    mlair.run(plot_list=remove_items(DEFAULT_PLOT_LIST, "PlotStationMap"))
 
 
 How to start with MLAir

docs/_source/index.rst

@@ -6,6 +6,7 @@
 Welcome to MLAir's documentation!
 ================================================
 
+This is the documation of the `MLAir package <https://gitlab.version.fz-juelich.de/toar/mlair>`_.
 
 .. toctree::
    :maxdepth: 2

mlair/__init__.py

 __version_info__ = {
-    'major': 0,
-    'minor': 12,
-    'micro': 1,
+    'major': 1,
+    'minor': 0,
+    'micro': 0,
 }
 
 from mlair.run_modules import RunEnvironment, ExperimentSetup, PreProcessing, ModelSetup, Training, PostProcessing
@@ -13,7 +13,7 @@ from mlair.model_modules import AbstractModelClass
 def get_version():
     assert set(__version_info__.keys()) >= {"major", "minor"}
     vers = [f"{__version_info__['major']}.{__version_info__['minor']}"]
-    if __version_info__["micro"]:
+    if "micro" in __version_info__:
         vers.append(f".{__version_info__['micro']}")
     return "".join(vers)
 

requirements.txt

+Cython==0.29.15
 absl-py==0.9.0
 astor==0.8.1
 atomicwrites==1.3.0
 attrs==19.3.0
-Cartopy==0.17.0
 certifi==2019.11.28
 chardet==3.0.4
 cloudpickle==1.3.0
 coverage==5.0.3
 cycler==0.10.0
-Cython==0.29.15
 dask==2.11.0
 fsspec==0.6.2
 gast==0.3.3
@@ -50,7 +49,6 @@ PyYAML==5.3
 requests==2.23.0
 scipy==1.4.1
 seaborn==0.10.0
---no-binary shapely Shapely==1.7.0
 six==1.11.0
 statsmodels==0.11.1
 tabulate
@@ -67,3 +65,5 @@ xarray==0.15.0
 zipp==3.1.0
 
 setuptools~=49.6.0
+Cartopy==0.18.0
+--no-binary shapely Shapely==1.7.0
\ No newline at end of file

requirements_gpu.txt

+Cython==0.29.15
 absl-py==0.9.0
 astor==0.8.1
 atomicwrites==1.3.0
 attrs==19.3.0
-#Cartopy==0.17.0
 certifi==2019.11.28
 chardet==3.0.4
 cloudpickle==1.3.0
 coverage==5.0.3
 cycler==0.10.0
-Cython==0.29.15
 dask==2.11.0
 fsspec==0.6.2
 gast==0.3.3
@@ -50,7 +49,6 @@ PyYAML==5.3
 requests==2.23.0
 scipy==1.4.1
 seaborn==0.10.0
---no-binary shapely Shapely==1.7.0
 six==1.11.0
 statsmodels==0.11.1
 tabulate
@@ -65,3 +63,6 @@ wcwidth==0.1.8
 Werkzeug==1.0.0
 xarray==0.15.0
 zipp==3.1.0
+
+#Cartopy==0.18.0
+--no-binary shapely Shapely==1.7.0
\ No newline at end of file

run_zam347.py

@@ -16,7 +16,7 @@ from mlair.workflows import DefaultWorkflowHPC
 
 def load_stations():
     try:
-        filename = 'German_background_stations.json'
+        filename = 'supplement/German_background_stations.json'
         with open(filename, 'r') as jfile:
             stations = json.load(jfile)
             logging.info(f"load station IDs from file: {filename} ({len(stations)} stations)")